writer-memory▌
yeachan-heo/oh-my-claudecode · updated May 12, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Persistent memory system designed for creative writers, with first-class support for Korean storytelling workflows.
Writer Memory - Agentic Memory System for Writers
Persistent memory system designed for creative writers, with first-class support for Korean storytelling workflows.
Overview
Writer Memory maintains context across Claude sessions for fiction writers. It tracks:
- Characters (캐릭터): Emotional arcs (감정궤도), attitudes (태도), dialogue tone (대사톤), speech levels
- World (세계관): Settings, rules, atmosphere, constraints
- Relationships (관계): Character dynamics and evolution over time
- Scenes (장면): Cut composition (컷구성), narration tone, emotional tags
- Themes (테마): Emotional themes (정서테마), authorial intent
All data persists in .writer-memory/memory.json for git-friendly collaboration.
Commands
| Command | Action |
|---|---|
/oh-my-claudecode:writer-memory init <project-name> |
Initialize new project memory |
/oh-my-claudecode:writer-memory status |
Show memory overview (character count, scene count, etc) |
/oh-my-claudecode:writer-memory char add <name> |
Add new character |
/oh-my-claudecode:writer-memory char <name> |
View character details |
/oh-my-claudecode:writer-memory char update <name> <field> <value> |
Update character field |
/oh-my-claudecode:writer-memory char list |
List all characters |
/oh-my-claudecode:writer-memory rel add <char1> <char2> <type> |
Add relationship |
/oh-my-claudecode:writer-memory rel <char1> <char2> |
View relationship |
/oh-my-claudecode:writer-memory rel update <char1> <char2> <event> |
Add relationship event |
/oh-my-claudecode:writer-memory scene add <title> |
Add new scene |
/oh-my-claudecode:writer-memory scene <id> |
View scene details |
/oh-my-claudecode:writer-memory scene list |
List all scenes |
/oh-my-claudecode:writer-memory theme add <name> |
Add theme |
/oh-my-claudecode:writer-memory world set <field> <value> |
Set world attribute |
/oh-my-claudecode:writer-memory query <question> |
Query memory naturally (Korean supported) |
/oh-my-claudecode:writer-memory validate <character> <dialogue> |
Check if dialogue matches character tone |
/oh-my-claudecode:writer-memory synopsis |
Generate emotion-focused synopsis |
/oh-my-claudecode:writer-memory export |
Export full memory as readable markdown |
/oh-my-claudecode:writer-memory backup |
Create manual backup |
Memory Types
캐릭터 메모리 (Character Memory)
Tracks individual character attributes essential for consistent portrayal:
| Field | Korean | Description |
|---|---|---|
arc |
감정궤도 | Emotional journey (e.g., "체념 -> 욕망자각 -> 선택") |
attitude |
태도 | Current disposition toward life/others |
tone |
대사톤 | Dialogue style (e.g., "담백", "직설적", "회피적") |
speechLevel |
말투 레벨 | Formality: 반말, 존댓말, 해체, 혼합 |
keywords |
핵심 단어 | Characteristic words/phrases they use |
taboo |
금기어 | Words/phrases they would never say |
emotional_baseline |
감정 기준선 | Default emotional state |
triggers |
트리거 | What provokes emotional reactions |
Example:
/writer-memory char add 새랑
/writer-memory char update 새랑 arc "체념 -> 욕망자각 -> 선택"
/writer-memory char update 새랑 tone "담백, 현재충실, 감정억제"
/writer-memory char update 새랑 speechLevel "해체"
/writer-memory char update 새랑 keywords "그냥, 뭐, 괜찮아"
/writer-memory char update 새랑 taboo "사랑해, 보고싶어"
세계관 메모리 (World Memory)
Establishes the universe your story inhabits:
| Field | Korean | Description |
|---|---|---|
setting |
배경 | Time, place, social context |
rules |
규칙 | How the world operates (magic systems, social norms) |
atmosphere |
분위기 | Overall mood and tone |
constraints |
제약 | What cannot happen in this world |
history |
역사 | Relevant backstory |
관계 메모리 (Relationship Memory)
Captures the dynamic between characters over time:
| Field | Description |
|---|---|
type |
Base relationship: romantic, familial, friendship, rivalry, professional |
status |
Current state: budding, stable, strained, broken, healing |
power_dynamic |
Who has the upper hand, if any |
events |
Timeline of relationship-changing moments |
tension |
Current unresolved conflicts |
intimacy_level |
Emotional closeness (1-10) |
Example:
/writer-memory rel add 새랑 해랑 romantic
/writer-memory rel update 새랑 해랑 "첫 키스 - 새랑 회피"
/writer-memory rel update 새랑 해랑 "해랑 고백 거절당함"
/writer-memory rel update 새랑 해랑 "새랑 먼저 손 잡음"
장면 메모리 (Scene Memory)
Tracks individual scenes and their emotional architecture:
| Field | Korean | Description |
|---|---|---|
title |
제목 | Scene identifier |
characters |
등장인물 | Who appears |
location |
장소 | Where it happens |
cuts |
컷 구성 | Shot-by-shot breakdown |
narration_tone |
내레이션 톤 | Narrative voice style |
emotional_tag |
감정 태그 | Primary emotions (e.g., "설렘+불안") |
purpose |
목적 | Why this scene exists in the story |
before_after |
전후 변화 | What changes for characters |
테마 메모리 (Theme Memory)
Captures the deeper meaning woven through your story:
| Field | Korean | Description |
|---|---|---|
name |
이름 | Theme identifier |
expression |
표현 방식 | How this theme manifests |
scenes |
관련 장면 | Scenes that embody this theme |
character_links |
캐릭터 연결 | Which characters carry this theme |
author_intent |
작가 의도 | What you want readers to feel |
Synopsis Generation (시놉시스)
The /synopsis command generates an emotion-focused summary using 5 essential elements:
5 Essential Elements (시놉시스 5요소)
-
주인공 태도 요약 (Protagonist Attitude Summary)
- How the protagonist approaches life/love/conflict
- Their core emotional stance
- Example: "새랑은 상실을 예방하기 위해 먼저 포기하는 사람"
-
관계 핵심 구도 (Core Relationship Structure)
- The central dynamic driving the story
- Power imbalances and tensions
- Example: "사랑받는 자와 사랑하는 자의 불균형"
-
정서적 테마 (Emotional Theme)
- The feeling the story evokes
- Not plot, but emotional truth
- Example: "손에 쥔 행복을 믿지 못하는 불안"
-
장르 vs 실제감정 대비 (Genre vs Real Emotion Contrast)
- Surface genre expectations vs. actual emotional content
- Example: "로맨스지만 본질은 자기수용 서사"
-
엔딩 정서 잔상 (Ending Emotional Aftertaste)
- The lingering feeling after the story ends
- Example: "씁쓸한 안도, 불완전한 해피엔딩의 여운"
Character Validation (캐릭터 검증)
The /validate command checks if dialogue matches a character's established voice.
What Gets Checked
| Check | Description |
|---|---|
| Speech Level | Does formality match? (반말/존댓말/해체) |
| Tone Match | Does the emotional register fit? |
| Keyword Usage | Uses characteristic words? |
| Taboo Violation | Uses forbidden words? |
| Emotional Range | Within character's baseline? |
| Context Fit | Appropriate for relationship and scene? |
Validation Results
- PASS: Dialogue is consistent with character
- WARN: Minor inconsistencies, may be intentional
- FAIL: Significant deviation from established voice
Example:
/writer-memory validate 새랑 "사랑해, 해랑아. 너무 보고싶었어."
Output:
[FAIL] 새랑 validation failed:
- TABOO: "사랑해" - character avoids direct declarations
- TABOO: "보고싶었어" - character suppresses longing expressions
- TONE: Too emotionally direct for 새랑's 담백 style
Suggested alternatives:
- "...왔네." (minimal acknowledgment)
- "늦었다." (deflection to external fact)
- "밥 먹었어?" (care expressed through practical concern)
Context Query (맥락 질의)
Natural language queries against memory, with full Korean support.
Example Queries
/writer-memory query "새랑은 이 상황에서 뭐라고 할까?"
/writer-memory query "규리의 현재 감정 상태는?"
/writer-memory query "해랑과 새랑의 관계는 어디까지 왔나?"
/writer-memory query "이 장면의 정서적 분위기는?"
/writer-memory query "새랑이 먼저 연락하는 게 맞아?"
/writer-memory query "해랑이 화났을 때 말투는?"
The system synthesizes answers from all relevant memory types.
Behavior
- On Init: Creates
.writer-memory/memory.jsonwith project metadata and empty collections - Auto-Backup: Changes are backed up before modification to
.writer-memory/backups/ - Korean-First: Emotion vocabulary uses Korean terms throughout
- Session Loading: Memory is loaded on session start for immediate context
- Git-Friendly: JSON formatted for clean diffs and collaboration
Integration
With OMC Notepad System
Writer Memory integrates with .omc/notepad.md:
- Scene ideas can be captured as notes
- Character insights from analysis sessions are preserved
- Cross-reference between notepad and memory
With Architect Agent
For complex character analysis:
Task(subagent_type="oh-my-claudecode:architect",
model="opus",
prompt="Analyze 새랑's arc across all scenes...")
Character Validation Pipeline
Validation pulls context from:
- Character memory (tone, keywords, taboo)
- Relationship memory (dynamics with dialogue partner)
- Scene memory (current emotional context)
- Theme memory (authorial intent)
Synopsis Builder
Synopsis generation aggregates:
- All character arcs
- Key relationship events
- Scene emotional tags
- Theme expressions
Examples
Full Workflow
# Initialize project
/writer-memory init 봄의 끝자락
# Add characters
/writer-memory char add 새랑
/writer-memory char update 새랑 arc "체념 -> 욕망자각 -> 선택"
/writer-memory char update 새랑 tone "담백, 현재충실"
/writer-memory char update 새랑 speechLevel "해체"
/writer-memory char add 해랑
/writer-memory char update 해랑 arc "확신 -> 동요 -> 기다림"
/writer-memory char update 해랑 tone "직진, 솔직"
/writer-memory char update 해랑 speechLevel "반말"
# Establish relationship
/writer-memory rel add 새랑 해랑 romantic
/writer-memory rel update 새랑 해랑 "첫 만남 - 해랑 일방적 호감"
/writer-memory rel update 새랑 해랑 "새랑 거절"
/writer-memory rel update 새랑 해랑 "재회 - 새랑 내적 동요"
# Set world
/writer-memory world set setting "서울, 현대, 20대 후반 직장인"
/writer-memory world set atmosphere "도시의 건조함 속 미묘한 온기"
# Add themes
/writer-memory theme add "포기하지 않는 사랑"
/writer-memory theme add "자기 보호의 벽"
# Add scene
/writer-memory scene add "옥상 재회"
# Query for writing
/writer-memory query "새랑은 이별 장면에서 어떤 톤으로 말할까?"
# Validate dialogue
/writer-memory validate 새랑 "해랑아, 그만하자."
# Generate synopsis
/writer-memory synopsis
# Export for reference
/writer-memory export
Quick Character Check
/writer-memory char 새랑
Output:
## 새랑
**Arc (감정궤도):** 체념 -> 욕망자각 -> 선택
**Attitude (태도):** 방어적, 현실주의
**Tone (대사톤):** 담백, 현재충실
**Speech Level (말투):** 해체
**Keywords (핵심어):** 그냥, 뭐, 괜찮아
**Taboo (금기어):** 사랑해, 보고싶어
**Relationships:**
- 해랑: romantic (intimacy: 6/10, status: healing)
**Scenes Appeared:** 옥상 재회, 카페 대화, 마지막 선택
Storage Schema
{
"version": "1.0",
"project": {
"name": "봄의 끝자락",
"genre": "로맨스",
"created": "2024-01-15T09:00:00Z",
"lastModified": "2024-01-20T14:30:00Z"
},
"characters": {
"새랑": {
"arc": "체념 -> 욕망자각 -> 선택",
"attitude": "방어적, 현실주의",
"tone": "담백, 현재충실",
"speechLevel": "해체",
"keywords": ["그냥", "뭐", "괜찮아"],
"taboo": ["사랑해", "보고싶어"],
"emotional_baseline": "평온한 무관심",
"triggers": ["과거 언급", "미래 약속"]
}
},
"world": {
"setting": "서울, 현대, 20대 후반 직장인",
"rules": [],
"atmosphere": "도시의 건조함 속 미묘한 온기",
"constraints": [],
"history": ""
},
"relationships": [
{
"id": "rel_001",
"from": "새랑",
"to": "해랑",
"type": "romantic",
"dynamHow to use writer-memory on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add writer-memory
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches writer-memory from GitHub repository yeachan-heo/oh-my-claudecode and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate writer-memory. Access the skill through slash commands (e.g., /writer-memory) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★46 reviews- ★★★★★Pratham Ware· Dec 28, 2024
Solid pick for teams standardizing on skills: writer-memory is focused, and the summary matches what you get after install.
- ★★★★★Li Bansal· Dec 28, 2024
writer-memory fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Hassan Liu· Dec 24, 2024
writer-memory has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Hassan Harris· Dec 16, 2024
writer-memory reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aanya Thomas· Dec 8, 2024
writer-memory is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ira Thomas· Nov 27, 2024
Useful defaults in writer-memory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kaira Thompson· Nov 19, 2024
Registry listing for writer-memory matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Hassan Zhang· Nov 7, 2024
We added writer-memory from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Mateo Srinivasan· Nov 3, 2024
Solid pick for teams standardizing on skills: writer-memory is focused, and the summary matches what you get after install.
- ★★★★★Hassan Khan· Oct 26, 2024
writer-memory fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
showing 1-10 of 46